Delegating to local llm

Skill isvlasov/rageatc-oss/plugins/rageatc-code-oss/skills/delegating-to-local-llm

Practical Claude Code / Cowork plugins for sharper thinking and structured problem-solving the slow way

Install

npx -y skills add isvlasov/rageatc-oss --skill delegating-to-local-llm

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

8 stars8 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Delegates a task to a local LLM running as a Pi coding-agent session in a herdr pane - the subagent is visible in herdr, can be steered mid-session, and costs no cloud tokens. Use when delegating work to a local model, spawning a Pi subagent, offloading a task to omlx (qwen, gemma), or running agent work offline. Not for Claude Code's own Agent tool or subagents inside Pi.

SKILL.md

3.9 KB, as published. Nobody here has run it

Delegating to a Local LLM

The subagent is an interactive Pi session pinned to a local omlx model, spawned in a herdr pane. herdr provides the whole control loop — spawn, state, read, send — and Pi's herdr integration reports working/blocked/idle automatically. The session stays visible and steerable; you own acceptance of its work.

Preflight

uname -m                                                  # arm64 required (omlx is Apple-Silicon MLX)
KEY=$(jq -r .auth.api_key ~/.omlx/settings.json)
curl -s --max-time 3 -H "Authorization: Bearer $KEY" http://127.0.0.1:8000/v1/models
which pi && herdr agent list >/dev/null && echo ok

curl fails -> omlx start; succeeds but lists no models -> models need downloading
pi or herdr missing, not arm64, or first run on this machine -> walk the user through references/setup.md

Delegate

Pick the model from the /v1/models response. The user's named choice wins; otherwise ask which model they prefer for the task. Memory headroom is model- and machine-specific: if omlx's prefill guard aborts mid-task ("Prefill context too large for available memory"), the model cannot handle the accumulated context on this machine — restart the task on a lighter model.
Spawn — short kebab task name; cwd is the project the task touches. Pin the pane to your own workspace — spawning defaults to whichever workspace the user has focused at that moment, which may not be yours:
```
WS=$(herdr pane get "$HERDR_PANE_ID" | jq -r '.result.pane.workspace_id')
herdr agent start <task-name> --cwd <dir> --workspace $WS --no-focus -- omlx launch pi --model <model-id> --api-key $KEY
```
Capture pane_id from the JSON response. (omlx launch also rewrites Pi's omlx provider config, so it is always current.)
Wait ready: herdr agent wait <task-name> --status idle --timeout 30000
Send the task, then submit it:
```
herdr agent send <task-name> "<task>"
sleep 1 && herdr pane send-keys <pane-id> enter
```
Task text is literal and single-line — shell-quote it, and make it self-contained: goal, relevant paths, done-criterion. Local models do best with one focused task.

Confirm submission with herdr agent wait <task-name> --status working --timeout 15000. A timeout usually means the Enter fired before the TUI was ready — send Enter again and re-wait; if it still hasn't started, read the pane to see what state the input is in.
Wait for completion: herdr agent wait <task-name> --status idle --timeout 600000 (10 min default — local generation is slow; scale to the task). The wait resolves on the next status change; read the status it reports: done means the run finished, blocked means Pi is asking a question (read the pane, answer via send + enter, wait again), errors also end in done — so always verify.
Verify: herdr agent read <task-name> --lines 60 for the subagent's account, then check the actual outputs (files, command results) yourself. Acceptance is your judgement, not its claim.
Steer if needed: repeat steps 4–5 into the same live session.
Hand over: summarise the result, leave the pane open, and tell the user the agent name — they can jump to it with herdr agent focus <task-name>. Close only when the user is done: herdr pane close <pane-id>.

Guardrails

One local subagent at a time — the model occupies unified memory.
Delegate self-contained tasks, not conversations that need your session's context.